Artificial Intelligence Engineer

AI Engineer – Dubai

• Partner with the Product Manager to design, develop, and implement secure, private AI agent platforms and supporting portals that automate business operations across multiple entities while ensuring compliance with internal data protection and security policies

• Architect, deploy, and manage self-hosted Large Language Model (LLM) environments (e.g., LLaMA, Mistral) without reliance on external or cloud-based AI APIs

• Design and maintain secure AI architectures incorporating data isolation, encryption, access controls, audit logging, and governance best practices

• Develop and support internal applications and user portals, including Single Sign-On (SSO), Role-Based Access Control (RBAC), and user management capabilities

• Implement and manage containerized and orchestrated environments using technologies such as Docker and Kubernetes

• Own the end-to-end AI platform lifecycle (MLOps), including deployment, monitoring, model versioning, performance optimization, and continuous improvement

• Design and develop AI agent ecosystems that support engineering processes, workflow automation, business operations, reporting, analytics, and decision-making

• Integrate AI solutions with enterprise platforms including Microsoft OneDrive, Jira, GitLab, repositories, and productivity tools to enable seamless cross-functional automation

• Build monitoring, reporting, and feedback mechanisms to measure agent performance, user adoption, operational efficiency, and business ROI

• Develop scalable, modular, and reusable solutions that can be leveraged across multiple business units and use cases

• Evaluate emerging AI technologies, frameworks, architectures, and models, translating technical innovations into practical business solutions

• Promote knowledge sharing by documenting best practices, reusable patterns, and lessons learned to strengthen AI engineering capabilities across the organization

• Provide technical leadership and mentorship to junior engineers while independently managing complex technical initiatives

• Collaborate closely with internal stakeholders to validate features, gather feedback, and continuously enhance AI-driven solutions

• Support commercial and client-facing activities by providing technical expertise, solution guidance, and maintaining technical relationships with customers

• Develop deep technical expertise in commercial AI products and architectures, contributing to their integration, customization, optimization, and delivery

• Design, implement, test, and deploy advanced AI capabilities in collaboration with Product Managers and Lead Engineers

• Translate business objectives and user requirements into scalable, actionable technical solutions, particularly within ambiguous or evolving environments

• Apply an iterative, experimentation-driven approach to solution development by validating assumptions, measuring outcomes, and continuously refining performance

• Contribute to, and where appropriate lead, architecture and solution design decisions while balancing scalability, performance, cost efficiency, and speed to market

• Communicate technical strategies, progress, risks, and trade-offs effectively to both technical and non-technical stakeholders, aligning engineering efforts with business objectives

• Work closely with internal users to test features, gather feedback, and drive continuous product improvement

• Provide technical support for business development and commercial initiatives, including client engagements, solution demonstrations, and technical consultations

Requirement

• Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.

• Minimum 8 years of hands-on experience in AI/ML engineering, ideally within, technology-driven organizations, or fast-paced product environments.

• Strong experience with Python

• Demonstrated ability to balance strategic thinking with hands-on execution, identifying long-term AI opportunities while delivering scalable, production-ready solutions.

• Strong analytical and data-driven mindset, with a deep understanding of the role of structured, enriched, and high-quality data in building effective AI systems.

• Proven experience developing, deploying, and optimizing AI/ML solutions in real-world business environments.

• Highly collaborative and proactive team player with a passion for knowledge sharing, continuous improvement, and contributing to collective success.

• Comfortable operating in dynamic, rapidly evolving environments where innovation, experimentation, and execution are equally valued.

• Strong problem-solving, communication, and stakeholder management skills, with the ability to translate complex technical concepts into business value.